I built an app that turns code or Swagger into interactive API docs

Hacker News

Greetings! Anindo here. I’ve been building a tool over the past few weeks to solve a problem that’s bugged me for years. Traditional API documentation. At every company I’ve worked at, we used Swagger UI or some OpenAPI wrapper. But reading those clunky, static docs always felt like exploring an uncharted jungle with an old, incomplete map. I’ve talked to dozens of devs who shared the same frustration. So, I've built DocPilot. A tool that turns your Swagger/OpenAPI specs or codebase into beautiful, interactive docs. Just upload your Swagger file or connect your GitHub repo and instantly get API docs with: - Mock servers - API Consoles - SDK Wrappers - FAQs based on your API If your team already uses Swagger, you’re 90% there. If not, DocPilot can parse your codebase directly. It’s still in early access (so expect some rough edges), but I’d love your feedback and ideas! Thank you so much for reading! Cheers, Anindo

Visit product View on Hacker NewsMay 20, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos

95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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